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Impact of enterprise artificial intelligence development on human capital structure

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  • Li, Zhe
  • Yang, Huiyu
  • Zhang, Tingting

Abstract

This study explores how artificial intelligence (AI) adoption influences low-skilled employment. Using data from Chinese A-share listed firms between 2012 and 2022, it reveals several key findings. First, AI adoption significantly reduces the number of low-skilled workers within firms. Second, digital transformation and human capital investment mediate this relationship, indicating that AI not only directly displaces low-skilled jobs but also indirectly influences employment by advancing digital capabilities and upskilling demands. Heterogeneity analysis further shows that these negative effects are more pronounced in non-state-owned enterprises and non-high-tech firms. The findings offer important insights for policymakers, business leaders, and workers, underscoring the need to align technological progress with workforce development in the AI era.

Suggested Citation

  • Li, Zhe & Yang, Huiyu & Zhang, Tingting, 2025. "Impact of enterprise artificial intelligence development on human capital structure," Finance Research Letters, Elsevier, vol. 82(C).
    • Handle: RePEc:eee:finlet:v:82:y:2025:i:c:s1544612325008591
    DOI: 10.1016/j.frl.2025.107600
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    as
    1. Yu, Feifei & Wang, Liting & Li, Xiaotong, 2020. "The effects of government subsidies on new energy vehicle enterprises: The moderating role of intelligent transformation," Energy Policy, Elsevier, vol. 141(C).
    2. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    3. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    4. Xiong, Mengzhi & Yang, Xuan & Huang, Bihui, 2025. "The impact of digital finance on the social governance capacity," Finance Research Letters, Elsevier, vol. 75(C).
    5. Yin, Hua & Yin, Xieyu & Wen, Fenghua, 2025. "Artificial intelligence and climate risk: A double machine learning approach," International Review of Financial Analysis, Elsevier, vol. 103(C).
    6. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    7. Dong, Zhenlin & Xin, Zijun & Liu, Dewen & Yu, Fangkun, 2024. "The impact of artificial intelligence application on company environmental investment in Chinese manufacturing companies," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    8. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    9. Bonaparte, Yosef, 2024. "Artificial Intelligence in Finance: Valuations and Opportunities," Finance Research Letters, Elsevier, vol. 60(C).
    10. Pan, Martin & Li, Daozheng & Wu, Hanrui & Lei, Pengfei, 2024. "Technological revolution and regulatory innovation: How governmental artificial intelligence adoption matters for financial regulation intensity," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    11. Liu, Jiaqi & Qin, Chuan & Chu, Xiaojing, 2025. "Development of corporate artificial intelligence and the quality of export products," Finance Research Letters, Elsevier, vol. 78(C).
    12. Weng, Min, 2025. "Green innovation through artificial intelligence technology: Enhancing environmental, social, and governance performance," Finance Research Letters, Elsevier, vol. 75(C).
    13. Gao, Yang & Liu, Siqiang & Yang, Lu, 2025. "Artificial intelligence and innovation capability: A dynamic capabilities perspective," International Review of Economics & Finance, Elsevier, vol. 98(C).
    14. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    15. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    16. Lei, Wei & Tang, Kaitao & Shao, Jingfeng & Ran, Feng, 2024. "Digital transformation, supply chain finance, and enterprise innovation," Finance Research Letters, Elsevier, vol. 70(C).
    17. Zhao, Na & Chen, Wenjiang, 2025. "How can artificial intelligence adoption enhance manufacturing firms' green management capability?," Finance Research Letters, Elsevier, vol. 81(C).
    18. Xie, Xiaoyu & Yan, Jun, 2024. "How does artificial intelligence affect productivity and agglomeration? Evidence from China's listed enterprise data," International Review of Economics & Finance, Elsevier, vol. 94(C).
    19. Zhong, Kai & Song, Liangrong, 2025. "Artificial intelligence adoption and corporate green innovation capability," Finance Research Letters, Elsevier, vol. 72(C).
    20. Gary S. Becker, 1964. "Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, First Edition," NBER Books, National Bureau of Economic Research, Inc, number beck-5.
    21. Li, Donghui & Zhang, Zhanxiang & Gao, Xin, 2024. "Does artificial intelligence deter greenwashing?," Finance Research Letters, Elsevier, vol. 67(PB).
    22. Yang, Chao & Huang, Cui, 2022. "Quantitative mapping of the evolution of AI policy distribution, targets and focuses over three decades in China," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    23. Minghui Han & Tianjian Yang & Junhao Zhong & Yilin Zhong, 2024. "AI applications and supply chain concentration," Applied Economics Letters, Taylor & Francis Journals, vol. 31(20), pages 2099-2103, November.
    24. Chang, Zhenghan, 2025. "Influence of artificial intelligence on the financial labor market," Finance Research Letters, Elsevier, vol. 80(C).
    25. Jin, Cheng-Xiao & Yu, Jia-Qi, 2025. "Does the popularization of artificial intelligence increase the risk of corporate digital responsibility?," Finance Research Letters, Elsevier, vol. 80(C).
    26. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    27. Bernd W. Wirtz & Jan C. Weyerer & Carolin Geyer, 2019. "Artificial Intelligence and the Public Sector—Applications and Challenges," International Journal of Public Administration, Taylor & Francis Journals, vol. 42(7), pages 596-615, May.
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    1. Han, Yikai & Huang, Yang, 2025. "Does artificial intelligence lead to human resource slack? Evidence from China," Finance Research Letters, Elsevier, vol. 84(C).

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